Operations | Monitoring | ITSM | DevOps | Cloud

When Covid-19 hit Romania, it was difficult for ordinary citizens to get good information about the pandemic and its escalating impact on the country. The government, presiding over one of the least developed healthcare infrastructures in the European Union, was releasing bulletins via PDF and text that were neither timely nor all that accurate. Into the breach stepped a team of six volunteers—five economists and a data scientist—operating out of Babes-Bolyai University.

Setting up Cloud Monitoring dashboards for your team can be time consuming because every team's needs are different. Picking the right metrics, using the right visualizations to represent these metrics, deciding what metrics can go on the same chart, and determining the right pre-processing steps for metrics requires background and experience that may not yet exist among your development and operations teams.

Yes, time travel is possible...through data. My ability to time travel began when I started coding at age 10. Back then, all of my code ran on my own little computer. Like many ten-year-olds, I coded to create and play games. I also coded cool graphics to accompany music to impress my friends and utilities for copying. I launched my first commercial website in 1996 and made 25 guilders, which was good money for a 15-year old. Life was so easy.

Modern software services are expected to be highly available, and running a service with minimal interruptions requires a certain amount of reliability-focused engineering work. At the same time, teams also need to build new features and improve existing ones, so that users are delighted and don’t churn.

The ability for security teams to integrate threat data into their operations substantially helps their organization identify potentially malicious endpoint and network events using indicators identified by other threat research teams. In this blog, we’ll cover how to ingest threat data with the Threat Intel Filebeat module. In future blog posts, we'll cover enriching threat data with the Threat ECS fieldset and operationalizing threat data with Elastic Security.

Though invisible to most users, APIs are the backbone of modern web applications. Developers love them because they facilitate complex integrations between systems and services. The business loves them because integrating disparate systems to create new products and services drives innovation and growth. The challenge with this transformative connectivity is the dependencies that exist between systems. API failure can result in performance degradation, data anomalies, or even system-wide outages.

The rise of public cloud services has enabled businesses to innovate faster, scale effortlessly, and adopt more advanced technologies easier than ever before. However, there’s a dark side to using public cloud services: complexity and cost. Public cloud services can scale to handle almost any workload, but in doing so, they can quickly generate unpredictable costs for your business.

This blog series is focused on observability into Kafka based applications. In the previous blogs, we discussed the key performance metrics to monitor different Kafka components in "Monitoring Kafka Performance with Splunk" and how to collect performance metrics using OpenTelemetry in "Collecting Kafka Performance Metrics with OpenTelemetry." In this blog, we'll cover how to enable distributed tracing for Kafka clients with OpenTelemetry and Splunk APM.

Many engineering organizations embrace the DevOps philosophy as a strategy for speeding software development and delivery while simultaneously improving the overall quality of the end product.